---
base_model: openai/whisper-small
datasets:
- mozilla-foundation/common_voice_11_0
language:
- ru
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper Small Ru - v4
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: ru
      split: test
      args: 'config: ru, split: test'
    metrics:
    - type: wer
      value: 11.993477274677849
      name: Wer
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Whisper Small Ru - v4

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2167
- Wer Ortho: 16.3879
- Wer: 11.9935

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.1695        | 0.4921 | 500  | 0.2079          | 17.6749   | 13.3434 |
| 0.1548        | 0.9843 | 1000 | 0.1894          | 16.4416   | 12.2240 |
| 0.0704        | 1.4764 | 1500 | 0.1878          | 16.1107   | 12.0106 |
| 0.0722        | 1.9685 | 2000 | 0.1854          | 15.7395   | 11.7887 |
| 0.0328        | 2.4606 | 2500 | 0.1927          | 15.7822   | 11.6404 |
| 0.0344        | 2.9528 | 3000 | 0.1929          | 15.5746   | 11.6060 |
| 0.0147        | 3.4449 | 3500 | 0.2059          | 15.6992   | 11.5141 |
| 0.0148        | 3.9370 | 4000 | 0.2046          | 15.7859   | 11.5962 |
| 0.0067        | 4.4291 | 4500 | 0.2169          | 16.0374   | 11.6784 |
| 0.0078        | 4.9213 | 5000 | 0.2167          | 16.3879   | 11.9935 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1